This paper presents an innovative approach to integrating natural neural networks into digital environments. By leveraging existing technologies and methodologies, the paper outlines a pathway for simulating the behavior of living neural networks within computational frameworks. Key elements include the exploration of brain cell chips, training methods, and imaging technologies such as MRI. The study aims to bridge the gap between conventional artificial neural networks and their natural counterparts, offering insights into understanding and controlling complex cognitive processes. The potential applications range from replicating animal behaviors to simulating human minds, with implications for fields such as robotics and neuroscience. Overall, the paper underscores the feasibility and desirability of digitally transferring natural neural networks for various practical and theoretical purposes.